← Back to Portfolio

03 — Regression Modeling

Simple and multivariable linear regression with residual diagnostics and short-window prediction generalization.

chiller-plant regression scikit-learn prediction
Pythonscikit-learnscipymatplotlib

Key Findings

  • Single-variable regression (kW vs OAT): R²=0.86, MSE=5,055
  • Multivariable regression (OAT, tons, occupancy): R²=0.98, MSE=1,099
  • 24-hour training window generalizes well to full dataset (R²=0.94)

Progressive regression modeling of chiller power consumption: from single-variable OAT regression to multivariable models with residual analysis. Tests whether a short 24-hour training window can generalize across the full operating period.

Notebook